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Examples on Clustering with R

August 25, 2011
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Examples on Clustering with R

R code examples on various clustering techniques are available as “Clustering in R” in Chapter 4 of R & Bioconductor Manual by Thomas Girke, UC Riverside. It provides R examples on - Hierarchical Clustering, including tree cutting/coloring and heatmaps, - … Continue reading →

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Numerical analysis for statisticians

August 25, 2011
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Numerical analysis for statisticians

“In the end, it really is just a matter of choosing the relevant parts of mathematics and ignoring the rest. Of course, the hard part is deciding what is irrelevant.” Somehow, I had missed the first edition of this book and thus I started reading it this afternoon with a newcomer’s eyes (obviously, I will

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computational difficulties [with notations]

August 25, 2011
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computational difficulties [with notations]

Here is an email I received from Umberto: I have a doubt regarding the tempered transitions method you considered in your JASA article with Celeux and Hurn. On page 961 you detail the several steps for building a proposal for a given distribution by simulating through l tempered power densities. I am slightly confused regarding

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le logiciel R

August 24, 2011
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le logiciel R

For once, here is a book review I wrote in French about the book Le logiciel R, written by Pierre Lafaye de Micheaux (Université de Montréal), Rémy Drouilhet (Université de Grenoble 2) and Benoît Liquet (Université de Bordeaux 2): Ce livre édité par Springer (dans la même collection que Le Choix Bayesien) propose une couverture

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expectation-propagation and ABC

August 23, 2011
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expectation-propagation and ABC

“It seems quite absurd to reject an EP-based approach, if the only alternative is an ABC approach based on summary statistics, which introduces a bias which seems both larger (according to our numerical examples) and more arbitrary, in the sense that in real-world applications one has little intuition and even less mathematical guidance on to

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Anonymising data

August 23, 2011
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Anonymising data

There are only three known jokes about statistics in the whole universe, so to complete the trilogy (see here and here for the other two), listen up: Three statisticians are on a train journey to a conference, and they get chatting to three epidemiologists who are also going to the same place. The epidemiologists are

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Time Series Analysis and Mining with R

August 23, 2011
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Time Series Analysis and Mining with R

Time series data are widely seen in analytics. Some examples are stock indexes/prices, currency exchange rates and electrocardiogram (ECG). Traditional time series analysis focuses on smoothing, decomposition and forecasting, and there are many R functions and packages available for those … Continue reading →

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Popular topics at the BioStar Q&A site

August 23, 2011
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Popular topics at the BioStar Q&A site

Which topics are the most popular at the BioStar bioinformatics Q&A site? One source of data is the tags used for questions. Tags are somewhat arbitrary of course, but fortunately BioStar has quite an active community, so “bad” tags are usually edited to improve them. Hint: if your question is “How to find SNPs”, then

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SIGKDD 2011 Conference — Day 1 (Graph Mining and David Blei/Topic Models)

August 22, 2011
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SIGKDD 2011 Conference — Day 1 (Graph Mining and David Blei/Topic Models)

I have been waiting for the KDD conference to come to California, and I was ecstatic to see it held in San Diego this year. AdMeld did an awesome job displaying KDD ads on the sites that I visit, sometimes multiple times per page. That’s good targeting! Mining and Learning on Graphs Workshop 2011 I had originally planned to attend the...

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Last and final on Richter’s painting

August 22, 2011
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Last and final on Richter’s painting

For a quick recap, Pierre and I supervised a team project at Ensae last year, on a statistical critique of the abstract painting 1024 Colours by painter Gerhard Richter. The four students, Clémence Bonniot, Anne Degrave, Guillaume Roussellet and Astrid Tricaud, did an outstanding job. Here is a selection of graphs and results they produced.

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